Industry
Future of work

How Companies are Using Machine Learning to Provide Better Customer Service

What underlines the success of your business? Or any business, for that matter. It’s how precisely you identify your target audience and develop an understanding of what pleases them. A majority of your target audience probably comprises of millennials or people born between 1981 and 1996 (who are today 23 to 38 years old). After all, millennials makeup almost half the working population in India, and have grabbed centre stage in the country’s consumption story, according to a report by Deloitte India and Retailers Association of India.

And, here’s one thing your business must know about millennials. It’s that they tend to prioritize experiences over products. In a survey by Harris Group, as many as 72% millennials said their spending decisions were based on experiences. So, if you thought you’d delight your existing or prospective customers with a cool product and its incredible features, it’s time to think again.

Businesses are increasingly focusing on customer experiences, which has created the need for innovative solutions in the customer service arena. In fact, this is one of the main reasons that companies choose the Veris visitor check-in software – to provide a touch-based-low-interaction digital experience to visitors!

Machine Learning Takes Customer Service a Step Further
Technological advancements and sophisticated software continue to play a key role in businesses looking to provide better customer service. The era of “choose 1 for English and 2 for Hindi” and having the customer answer a plethora of question for verification will soon be behind us. Instead, technology will track a customer’s interaction at various touch points. So, if a customer has communicated with a chatbot on your website, a customer care executive at the call centre already knows the question the customer is seeking an answer to. Advanced voice/ face identification software can be used for verification.

Hyper-Personalized Interactions
It can track customer activity real-time and retain all information about a customer from every touch point, be it the official website, SMS, WhatsApp or Facebook Messenger. The system can then send out personalized notifications to customer support executives on call with a customer. For instance, if the system knows that the customer had spent time reading a blog post on the company’s website, it can inform the customer support executive to offer a discount on that specific product or service.

DIY Resolutions
Machine learning can analyze previous interactions to help a customer resolve the query without having to call the customer care and predict customer needs. Depending on this, the system can recommend articles or videos that can resolve customer queries.

Proactive Assistance
If a customer searches for something on your company website, the system can proactively send out emails answering queries and recommending next steps.

Improve Processes and Even the Product
Machine learning can analyze massive amounts of data and present insights to improve processes. It can identify the main pain-points of customers and help companies make product improvements.

Customer Profiling
With access to continuous data, machine learning can create different customer profiles and make predictions. For instance, it can identify whether a customer would prefer to receive a call, an email or a WhatsApp message.

Machine learning is more than a buzzword. It is helping companies provide impressive customer support, while also reducing call center costs and identifying up-selling and cross-selling opportunities.

We, too, understand the importance of improving customer experience, increasing process efficiency and providing valuable insight. These are the very tenets on which the Veris visitor software is based.

‘Work the talk’ is an initiative by Veris that empowers businesses to co-create workplaces of the future. In this podcast series, we talk with industry leaders to gain insights about the latest trends, challenges, and opportunities impacting workplaces across industries.